43 citations · 102 across the 7 of their papers we have counts for
8 papers
Computationally efficient likelihood inference in exponential families when the maximum likelihood estimator does not exist
Daniel J. Eck, Charles J. Geyer
In a regular full exponential family, the maximum likelihood estimator (MLE) need not exist in the traditional sense. However, the MLE may exist in the completion of the exponentia…
Automatic Response Category Combination in Multinomial Logistic Regression
Bradley S. Price, Charles J. Geyer, Adam J. Rothman
We propose a penalized likelihood method that simultaneously fits the multinomial logistic regression model and combines subsets of the response categories. The penalty is non diff…
Combining Envelope Methodology and Aster Models for Variance Reduction in Life History Analyses
Daniel J. Eck, Charles J. Geyer, R. Dennis Cook
Precise estimation of expected Darwinian fitness, the expected lifetime number of offspring of organism, is a central component of life history analysis. The aster model serves as…
Local adaptation and genetic effects on fitness: Calculations for exponential family models with random effects
Charles J. Geyer, Caroline E. Ridley, Robert G. Latta +2
Random effects are implemented for aster models using two approximations taken from Breslow and Clayton [J. Amer. Statist. Assoc. 88 (1993) 9-25]. Random effects are analytically i…
Ridge Fusion in Statistical Learning
Bradley S. Price, Charles J. Geyer, Adam J. Rothman
We propose a penalized likelihood method to jointly estimate multiple precision matrices for use in quadratic discriminant analysis and model based clustering. A ridge penalty and…
Variable transformation to obtain geometric ergodicity in the random-walk Metropolis algorithm
Leif T. Johnson, Charles J. Geyer
A random-walk Metropolis sampler is geometrically ergodic if its equilibrium density is super-exponentially light and satisfies a curvature condition [Stochastic Process. Appl. 85…